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Only 30% of Companies are Prepared to Scale with AI

Elizabeth Greenberg

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scaling ai
New research reveals a wide gap between AI experimentation and enterprise-wide adoption, highlighting the barriers and strategies for the next wave of AI transformation.

Enterprise leaders are eager to move beyond AI experimentation and unlock scalable value.

However, new research from Kore.ai, a global leader in enterprise AI, reveals a critical gap: while 71% of companies are actively using or piloting AI, only 30% are prepared to scale — potentially slowing the momentum of the next wave of enterprise AI adoption.

The new report, Practical Insights from AI Leaders, surveyed 1,000 senior business and technology leaders across 10 countries. It finds that 89% of respondents say their companies plan to increase AI investments in 2025, with three-quarters of all respondents planning to allocate up to half of their IT budgets to AI initiatives.

Scaling AI, however, remains a major hurdle, hampered by three key challenges.

These include a lack of AI talent (44%), unpredictable costs associated with large language models (42%), and persistent concerns around data privacy and regulatory compliance (41%).

The report highlights the top strategies AI leaders are adopting to overcome these hurdles as well. First, leaders identified four critical investment areas that underpin scalability: hiring internal and external AI talent (66%), improving data quality (51%), strengthening solution security (40%) and upgrading IT infrastructure (37%). AI initiatives grounded in these focus areas are more likely to deliver sustainable, enterprise-wide value.

Secondly, organisations are becoming more intentional about where and how they apply AI. Strikingly, 72% of respondents prefer to buy and customise AI solutions rather than build them from scratch internally, prioritising ease of deployment, regulatory compliance, solution quality, and integration.

The survey indicates that successful implementations have GenAI, LLMs, and conversational AI technologies already in production or scaling, while emerging areas like multi-modal AI, RAG, and agentic AI are gaining traction through active experimentation and pilots.

“AI is no longer experimental, it’s foundational,” said Raj Koneru, Founder and CEO of Kore.ai.

“We’re seeing businesses reimagine how they operate, innovate, and grow—and AI is at the heart of this transformation.

“The future enterprise will have AI embedded across every function, with humans and intelligent agents working side by side. To prepare for this future, organisations must prioritise data readiness, build scalable infrastructure, implement responsible governance, and invest in empowering their workforce to thrive alongside AI.”


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An AI Scaling Strategy

To scale AI successfully, organisations must focus on measurable ROI. Senior leaders identified the top success indicators as operational efficiency, output quality, employee productivity, customer satisfaction, and time-to-completion.

They identified three key application areas for AI: AI for business process orchestration (44%), including automation, operations, compliance and risk management; AI for workforce productivity (31%), like for task automation, information discovery, and employee support; and AI for customer experience (24%) such as support and self-service.

While 71% of AI leaders report that their organisations are actively experimenting with or using AI across multiple departments and use cases, focusing on the right applications—and having an organisation-wide AI strategy from the start—is proving essential for successful scaling.

Elizabeth Greenberg

Staff Writer

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